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Using closure tables to enable cross-querying of ontologies in database-driven applications

机译:使用闭合表以在数据库驱动的应用程序中开发跨查​​询本体

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We demonstrate that closure tables are an effective data structure for developing database-driven applications that query biomedical ontologies and that require cross-querying between multiple ontologies. A closure table stores all available paths within a tree, even those without a direct parent-child relationship; additionally, a node can have multiple ancestors which gives the foundation for supporting linkages between controlled ontologies. We augment the meta-data structure of the ICD9 and ICD10 ontologies included in i2b2, an open source query tool for identifying patient cohorts, to utilize a closure table. We describe our experiences in incorporating existing mappings between ontologies to enable clinical and health researchers to identify patient populations using the ontology that best matches their preference and expertise.
机译:我们演示了封闭表是一种有效的数据结构,用于开发查询生物医学本体的数据库驱动的应用程序,并且需要在多个本体之间进行交叉查询。关闭表将所有可用路径存储在树中,即使是那些没有直接亲子关系的路径;另外,节点可以具有多个祖先,它给出了支持受控本体之间的联系的基础。我们增强了I2B2中包含的ICD9和ICD10本体的元数据结构,是用于识别患者群体的开源查询工具,用于利用闭合表。我们描述了我们在本体之间的现有映射结合在本体中的现有映射,以使临床和健康研究人员使用最佳符合他们的偏好和专业知识的本体来识别患者人群。

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